Artificial intelligence (AI) has been making significant progress in the healthcare industry. Anesthesiology is one field that is seeing remarkable advancements in AI. Anesthesia providers can use AI to improve patient outcomes by providing personalized treatment plans, automating routine tasks, and reducing the risk of complications. In this blog post, we will discuss three current and three future uses of AI in anesthesiology.
Use of these advancements depends greatly upon the technology available in an individual hospital or surgical center. Many, if not most, anesthesia care performed in the United States is done in conjunction with some form of technology assistance (computer charting, digital readings on anesthesia machines, etc). However, as we step into the future of medicine we must ask “how will AI improve anesthesia care, and what will a be changing in our Operating Rooms for the better?”
Current Uses of AI in Anesthesiology
1. Automated Charting
AI can assist in automated charting by analyzing real-time data from the patient and anesthesia machine. Anesthetists can input the patient’s vital signs into the anesthesia machine, and the AI software can capture this data and update the electronic health record (EHR) automatically. This eliminates the need for manual charting, reducing errors and improving efficiency.
2. Personalized Anesthesia Care
AI can help the anesthesia provider provide personalized anesthesia care by analyzing patient data such as vital signs, medical history, and medication use. The AI software can predict how the patient will respond to anesthesia and adjust the dosage accordingly. This can lead to safer and more effective anesthesia care, reducing the risk of complications and adverse events.
3. Predictive Analysis
AI can use predictive analytics to identify patients at high risk for postoperative complications such as nausea, vomiting, and pain. By analyzing patient data, the AI software can predict which patients are at risk and recommend preventive measures, such as administering anti-nausea medication before the surgery. This can lead to better patient outcomes and reduced healthcare costs.
Future Uses of AI in Anesthesiology
1. Automated Machine Learning
Automated machine learning (AutoML) can help anesthesia providers develop predictive models more quickly and efficiently. AutoML can analyze large datasets and generate machine learning models automatically, reducing the time and effort required to develop predictive models. This can lead to more accurate predictions and better patient outcomes.
2. Natural Language Processing
Natural language processing (NLP) can help anesthesia providers extract insights from unstructured clinical data such as physician notes, imaging reports, and patient feedback. NLP can analyze large volumes of text data and extract key information, such as the patient’s medical history, allergies, and previous surgeries. This can provide a more comprehensive view of the patient’s health status and improve decision-making.
3. Real-time Monitoring
Perhaps the most exciting potential future development is AI enabled real-time monitoring of patient health status during surgery. By analyzing real-time data from the patient and anesthesia machine, AI can detect early warning signs of potential complications and alert the medical team. This can enable timely intervention and prevent adverse events.
Real-time AI monitoring is becoming essential in many fields, and medical care can benefit greatly from this technology. Human real-time assessment is still essential in anesthesia care due to the need for quick action in a potential surgical emergency, but humans can only process so much information at once. With the help of AI, all data and patient information can be assessed nearly simultaneously to alert the anesthesia provider immediately.
AI is transforming anesthesiology by improving patient outcomes, reducing healthcare costs, and increasing efficiency. With the current and future uses of AI anesthesia and all medical care will continue to evolve. We should expect to see further advancements in anesthesiology and other areas of healthcare in the near future.
References:
- Bowdle, T. A. (2018). The future of anesthesiology: should we be worried? Anesthesia & Analgesia, 127(4), 803-807.
- Kurz, A., Sessler, D. I., & McCoy, M. (2018). The future of anesthesia: should anesthesiologists be worried?. Anesthesia & Analgesia, 127(4), 749-753.
- Dexter, F., Epstein, R. H., & Thenuwara, K. (2019). Automated documentation of all cases using the anesthesia information management system. Anesthesia & Analgesia, 129(3), 738-743.
Check out more sticker from CoryB CRNA! https://lifeofcoryb.com/2023/02/15/5-best-ways-to-prepare-for-crna-school/
Don’t forget to stop by CoryB Designs at Redbubble to get your anesthesia gear… just click the link 👉CoryB Designs
CoryB CRNA 